The present invention relates to fluoroscopic image sequences, and more particularly to detecting coronary vessel layers from fluoroscopic image sequences.
Angiography is a medical imaging technique in which X-ray images are used to visualize internal blood filled structures, such as arteries, veins, and the heart chambers. Since blood has the same radiodensity as the surrounding tissues, these blood-filled structures cannot be differentiated from the surrounding tissue using conventional radiology. Thus, in angiography, a contrast agent is added to the blood, usually via a catheter, to make the blood vessels visible via X-ray. In many angiography procedures, X-ray images are taken over a period of time, which results in a sequence of fluoroscopic images, which show the motion of the blood over the period of time. Such fluoroscopic image sequences contain useful information that can be difficult to decipher due to the collapsing of 3-dimensional information into the 2-dimensional images.
In traditional computer imaging problems of motion estimation, occlusion handling or motion segmentation are typically the main concerns. Accordingly, traditional techniques for extracting objects of interest from image sequences typically use intensity based approaches to differentiate between objects in the image sequences. However, such traditional techniques can yield erroneous results in medical image sequences, such as fluoroscopic image sequences, which are generated using the phenomenon of transparency. Since various internal structures have different levels of transparency in the fluoroscopic images, these structures can overlap, and it may be difficult to accurately distinguish between these structures in the fluoroscopic image sequences using the traditional intensity based approaches.